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An in-coordinate interval adaptive Kalman filtering algorithm for INS/GPS/SMNS

机译:INS / GPS / SMNS的坐标间隔自适应卡尔曼滤波算法

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This paper proposes an in-coordinate interval adaptive Kalman filter for INS/GPS/SMNS (Inertial Navigation System/Global Position System/Scene Matching Navigation System) integrated navigation system in which SMNS has the characteristics of randomness and in-coordinate interval when it outputs the reliable positioning information. The proposed filter sets the period of the INS parameters analysis as reference, the periods of parameters output of GPS and SMNS are adjusted to be integral multiple of the INS analysis period by interpolation or extrapolation method; The system is updated only based on INS information when the observation information don't reach, it is updated based on all navigation information when the observation information reach; In addition, this method can overcome the drawbacks of the traditional Kalman filtering method when the system measurement noise is unknown. The proposed algorithm and the method proposed by reference [8] are applied to INS/GPS/SMNS integrated navigation system. Simulation results show that the in-coordinate interval adaptive Kalman filter outperforms the traditional Kalman filter.
机译:提出了一种用于惯性导航系统/全球定位系统/场景匹配导航系统的INS / GPS / SMNS组合导航系统的坐标间隔自适应卡尔曼滤波器,其中SMNS输出时具有随机性和坐标间隔的特征。可靠的定位信息。提出的滤波器以INS参数分析周期为参考,通过插值或外推法将GPS和SMNS的参数输出周期调整为INS分析周期的整数倍。当观测信息未到达时,仅根据INS信息进行系统更新;观测信息未到达时,将根据所有导航信息进行系统更新;另外,当系统测量噪声未知时,该方法可以克服传统卡尔曼滤波方法的弊端。所提出的算法和参考文献[8]提出的方法被应用于INS / GPS / SMNS组合导航系统。仿真结果表明,坐标间隔自适应卡尔曼滤波器优于传统的卡尔曼滤波器。

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